Enhanced command selection in a networked computing environment

ABSTRACT

Embodiments of the present invention provide an approach for identifying commands for virtual resource instances in a networked computing environment (e.g., a cloud computing environment). Specifically, in a typical embodiment, a set of commands for an instance of a virtual resource may be received in a computer memory medium or the like. The commands may then be analyzed and information pertaining to the commands may be stored in a computer storage device or the like. When a user/requester later wishes to identify a command to be utilized for another instance of the virtual resource, the requester can access the information and be provided with a set of suggested commands that are typically utilized for similar and/or previous instances of the virtual resource.

CROSS REFERENCE TO RELATED APPLICATIONS

This application is a continuation of, and claims the benefit of,co-pending and co-owned U.S. patent application Ser. No. 13/875,464,filed May 2, 2013, having attorney docket number END920120222US1, theentire contents of which are herein incorporated by reference. Thisapplication is also related in some aspects to the commonly owned andissued U.S. Pat. No. 8,838,799, issued Sep. 16, 2014, and which isassigned docket number END920110262US1. This application is also relatedin some aspects to the commonly owned and co-pending U.S. patentapplication Ser. No. 14/330,043, filed Jul. 14, 2014, and which isassigned docket number END920110262US2.

TECHNICAL FIELD

In general, embodiments of the present invention provide an approach forvirtual resource instance management. Specifically, embodiments of thepresent invention relate to an approach for identifying commands forvirtual resource instances in a networked computing environment (e.g., acloud computing environment).

BACKGROUND

The networked computing environment (e.g., cloud computing environment)is an enhancement to the predecessor grid environment, whereby multiplegrids and other computation resources may be further enhanced by one ormore additional abstraction layers (e.g., a cloud layer), thus makingdisparate devices appear to an end-consumer as a single pool of seamlessresources. These resources may include such things as physical orlogical computing engines, servers and devices, device memory, andstorage devices, among others.

In networked computing environments, customers may instantiate instancesof virtual images or other virtual resources. Challenges may exist,however, in identifying how and where to interact with a newlyinstantiated instance. Specifically, it may be difficult for auser/customer to select what commands to utilize with a particularinstance.

SUMMARY

In general, embodiments of the present invention provide an approach foridentifying commands for virtual resource instances in a networkedcomputing environment (e.g., a cloud computing environment).Specifically, in a typical embodiment, a set of commands for an instanceof a virtual resource may be received in a computer memory medium or thelike. The commands may then be analyzed and information pertaining tothe commands may be stored in a computer storage device or the like.When a user/requester later wishes to identify a command to be utilizedfor another instance of the virtual resource, the requester can accessthe information and be provided with a set of suggested commands thatare typically utilized for similar and/or previous instances of thevirtual resource.

A first aspect of the present invention provides a computer-implementedmethod for identifying commands for virtual resource instances in anetworked computing environment, comprising: analyzing a set of commandsto identify information pertaining to the set of commands, theinformation identifying at least one of the following: the set ofcommands, a date/time stamp associated with the set of commands,relationship artifacts associated with the set of commands, and a set oftags associated with the set of commands; receiving, from a requester, arequest to access at least a subset of the information; retrieving theat least a subset of the information from a computer storage device togenerate a set of suggested commands; and providing the set of suggestedcommands to the requester.

A second aspect of the present invention provides a system foridentifying commands for virtual resource instances in a networkedcomputing environment, comprising: a memory medium comprisinginstructions; a bus coupled to the memory medium; and a processorcoupled to the bus that when executing the instructions causes thesystem to: analyze a set of commands to identify information pertainingto the set of commands, the information identifying at least one of thefollowing: the set of commands, a date/time stamp associated with theset of commands, relationship artifacts associated with the set ofcommands, and a set of tags associated with the set of commands;receive, from a requester, a request to access at least a subset of theinformation; retrieve the at least a subset of the information from acomputer storage device to generate a set of suggested commands; andprovide the set of suggested commands to the requester.

A third aspect of the present invention provides a computer programproduct for identifying commands for virtual resource instances in anetworked computing environment, the computer program product comprisinga computer readable storage media, and program instructions stored onthe computer readable storage media, to: analyze a set of commands toidentify information pertaining to the set of commands, the informationidentifying at least one of the following: the set of commands, adate/time stamp associated with the set of commands, relationshipartifacts associated with the set of commands, and a set of tagsassociated with the set of commands; receive, from a requester, arequest to access at least a subset of the information; retrieve the atleast a subset of the information from a computer storage device togenerate a set of suggested commands; and provide the set of suggestedcommands to the requester.

A fourth aspect of the present invention provides a method for deployinga system for identifying commands for virtual resource instances in anetworked computing environment, comprising: providing a computerinfrastructure being operable to: analyze a set of commands to identifyinformation pertaining to the set of commands, the informationidentifying at least one of the following: the set of commands, adate/time stamp associated with the set of commands, relationshipartifacts associated with the set of commands, and a set of tagsassociated with the set of commands; receive, from a requester, arequest to access at least a subset of the information; retrieve the atleast a subset of the information from a computer storage device togenerate a set of suggested commands; and provide the set of suggestedcommands to the requester.

BRIEF DESCRIPTION OF THE DRAWINGS

These and other features of this invention will be more readilyunderstood from the following detailed description of the variousaspects of the invention taken in conjunction with the accompanyingdrawings in which:

FIG. 1 depicts a cloud computing node according to an embodiment of thepresent invention;

FIG. 2 depicts a cloud computing environment according to an embodimentof the present invention;

FIG. 3 depicts abstraction model layers according to an embodiment ofthe present invention;

FIG. 4 depicts a system diagram according to an embodiment of thepresent invention;

FIG. 5 depicts a method flow diagram according to an embodiment of thepresent invention;

FIG. 6 depicts an example process flow according to an embodiment of thepresent invention;

FIG. 7 depicts a method flow diagram according to an embodiment of thepresent invention;

FIG. 8 depicts a method flow diagram according to an embodiment of thepresent invention;

FIG. 9 depicts a method flow diagram according to an embodiment of thepresent invention; and

FIG. 10 depicts a method flow diagram according to an embodiment of thepresent invention.

The drawings are not necessarily to scale. The drawings are merelyschematic representations, not intended to portray specific parametersof the invention. The drawings are intended to depict only typicalembodiments of the invention, and therefore should not be considered aslimiting the scope of the invention. In the drawings, like numberingrepresents like elements.

DETAILED DESCRIPTION

Illustrative embodiments will now be described more fully herein withreference to the accompanying drawings, in which embodiments are shown.This disclosure may, however, be embodied in many different forms andshould not be construed as limited to the embodiments set forth herein.Rather, these embodiments are provided so that this disclosure will bethorough and complete and will fully convey the scope of this disclosureto those skilled in the art. In the description, details of well-knownfeatures and techniques may be omitted to avoid unnecessarily obscuringthe presented embodiments.

The terminology used herein is for the purpose of describing particularembodiments only and is not intended to be limiting of this disclosure.As used herein, the singular forms “a”, “an”, and “the” are intended toinclude the plural forms as well, unless the context clearly indicatesotherwise. Furthermore, the use of the terms “a”, “an”, etc., do notdenote a limitation of quantity, but rather denote the presence of atleast one of the referenced items. The term “set” is intended to mean aquantity of at least one. It will be further understood that the terms“comprises” and/or “comprising”, or “includes” and/or “including”, whenused in this specification, specify the presence of stated features,regions, integers, steps, operations, elements, and/or components, butdo not preclude the presence or addition of one or more other features,regions, integers, steps, operations, elements, components, and/orgroups thereof.

Embodiments of the present invention provide an approach for identifyingcommands for virtual resource instances in a networked computingenvironment (e.g., a cloud computing environment). Specifically, in atypical embodiment, a set of commands for an instance of a virtualresource may be received in a computer memory medium or the like. Thecommands may then be analyzed and information pertaining to the commandsmay be stored in a computer storage device or the like. When auser/requester later wishes to identify a command to be utilized foranother instance of the virtual resource, the requester can access theinformation and be provided with a set of suggested commands that aretypically utilized for similar and/or previous instances of the virtualresource.

It is understood in advance that although this disclosure includes adetailed description of cloud computing, implementation of the teachingsrecited herein are not limited to a cloud computing environment. Rather,embodiments of the present invention are capable of being implemented inconjunction with any other type of computing environment now known orlater developed.

Cloud computing is a model of service delivery for enabling convenient,on-demand network access to a shared pool of configurable computingresources (e.g. networks, network bandwidth, servers, processing,memory, storage, applications, virtual machines, and services) that canbe rapidly provisioned and released with minimal management effort orinteraction with a provider of the service. This cloud model may includeat least five characteristics, at least three service models, and atleast four deployment models.

Characteristics are as follows. On-demand self-service: a cloud consumercan unilaterally provision computing capabilities, such as server timeand network storage, as needed, automatically without requiring humaninteraction with the service's provider.

Broad network access: capabilities are available over a network andaccessed through standard mechanisms that promote use by heterogeneousthin or thick client platforms (e.g., mobile phones, laptops, and PDAs).

Resource pooling: the provider's computing resources are pooled to servemultiple consumers using a multi-tenant model, with different physicaland virtual resources dynamically assigned and reassigned according todemand. There is a sense of location independence in that the consumergenerally has no control or knowledge over the exact location of theprovided resources but may be able to specify location at a higher levelof abstraction (e.g., country, state, or datacenter).

Rapid elasticity: capabilities can be rapidly and elasticallyprovisioned, in some cases automatically, to quickly scale out andrapidly released to quickly scale in. To the consumer, the capabilitiesavailable for provisioning often appear to be unlimited and can bepurchased in any quantity at any time.

Measured service: cloud systems automatically control and optimizeresource use by leveraging a metering capability at some level ofabstraction appropriate to the type of service (e.g., storage,processing, bandwidth, and active consumer accounts). Resource usage canbe monitored, controlled, and reported providing transparency for boththe provider and consumer of the utilized service.

Service Models are as follows:

Software as a Service (SaaS): the capability provided to the consumer isto use the provider's applications running on a cloud infrastructure.The applications are accessible from various client devices through athin client interface such as a web browser (e.g., web-based email). Theconsumer does not manage or control the underlying cloud infrastructureincluding network, servers, operating systems, storage, or evenindividual application capabilities, with the possible exception oflimited consumer-specific application configuration settings.

Platform as a Service (PaaS): the capability provided to the consumer isto deploy onto the cloud infrastructure consumer-created or acquiredapplications created using programming languages and tools supported bythe provider. The consumer does not manage or control the underlyingcloud infrastructure including networks, servers, operating systems, orstorage, but has control over the deployed applications and possiblyapplication-hosting environment configurations.

Infrastructure as a Service (IaaS): the capability provided to theconsumer is to provision processing, storage, networks, and otherfundamental computing resources where the consumer is able to deploy andrun arbitrary software, which can include operating systems andapplications. The consumer does not manage or control the underlyingcloud infrastructure but has control over operating systems, storage,deployed applications, and possibly limited control of select networkingcomponents (e.g., host firewalls).

Deployment Models are as follows:

Private cloud: the cloud infrastructure is operated solely for anorganization. It may be managed by the organization or a third party andmay exist on-premises or off-premises.

Community cloud: the cloud infrastructure is shared by severalorganizations and supports a specific community that has shared concerns(e.g., mission, security requirements, policy, and complianceconsiderations). It may be managed by the organizations or a third partyand may exist on-premises or off-premises.

Public cloud: the cloud infrastructure is made available to the generalpublic or a large industry group and is owned by an organization sellingcloud services.

Hybrid cloud: the cloud infrastructure is a composition of two or moreclouds (private, community, or public) that remain unique entities butare bound together by standardized or proprietary technology thatenables data and application portability (e.g., cloud bursting forload-balancing between clouds).

A cloud computing environment is service oriented with a focus onstatelessness, low coupling, modularity, and semantic interoperability.At the heart of cloud computing is an infrastructure comprising anetwork of interconnected nodes.

Referring now to FIG. 1, a schematic of an example of a cloud computingnode is shown. Cloud computing node 10 is only one example of a suitablecloud computing node and is not intended to suggest any limitation as tothe scope of use or functionality of embodiments of the inventiondescribed herein. Regardless, cloud computing node 10 is capable ofbeing implemented and/or performing any of the functionality set forthhereinabove.

In cloud computing node 10, there is a computer system/server 12, whichis operational with numerous other general purpose or special purposecomputing system environments or configurations. Examples of well-knowncomputing systems, environments, and/or configurations that may besuitable for use with computer system/server 12 include, but are notlimited to, personal computer systems, server computer systems, thinclients, thick clients, hand-held or laptop devices, multiprocessorsystems, microprocessor-based systems, set top boxes, programmableconsumer electronics, network PCs, minicomputer systems, mainframecomputer systems, and distributed cloud computing environments thatinclude any of the above systems or devices, and the like.

Computer system/server 12 may be described in the general context ofcomputer system-executable instructions, such as program modules, beingexecuted by a computer system. Generally, program modules may includeroutines, programs, objects, components, logic, data structures, and soon that perform particular tasks or implement particular abstract datatypes. Computer system/server 12 may be practiced in distributed cloudcomputing environments where tasks are performed by remote processingdevices that are linked through a communications network. In adistributed cloud computing environment, program modules may be locatedin both local and remote computer system storage media including memorystorage devices.

As shown in FIG. 1, computer system/server 12 in cloud computing node 10is shown in the form of a general-purpose computing device. Thecomponents of computer system/server 12 may include, but are not limitedto, one or more processors or processing units 16, a system memory 28,and a bus 18 that couples various system components including systemmemory 28 to processor 16.

Bus 18 represents one or more of any of several types of bus structures,including a memory bus or memory controller, a peripheral bus, anaccelerated graphics port, and a processor or local bus using any of avariety of bus architectures. By way of example, and not limitation,such architectures include Industry Standard Architecture (ISA) bus,Micro Channel Architecture (MCA) bus, Enhanced ISA (EISA) bus, VideoElectronics Standards Association (VESA) local bus, and PeripheralComponent Interconnects (PCI) bus.

Computer system/server 12 typically includes a variety of computersystem readable media. Such media may be any available media that isaccessible by computer system/server 12, and it includes both volatileand non-volatile media, removable and non-removable media.

System memory 28 can include computer system readable media in the formof volatile memory, such as random access memory (RAM) 30 and/or cachememory 32. Computer system/server 12 may further include otherremovable/non-removable, volatile/non-volatile computer system storagemedia. By way of example only, storage system 34 can be provided forreading from and writing to a non-removable, non-volatile magnetic media(not shown and typically called a “hard drive”). Although not shown, amagnetic disk drive for reading from and writing to a removable,non-volatile magnetic disk (e.g., a “floppy disk”), and an optical diskdrive for reading from or writing to a removable, non-volatile opticaldisk such as a CD-ROM, DVD-ROM, or other optical media can be provided.In such instances, each can be connected to bus 18 by one or more datamedia interfaces. As will be further depicted and described below,memory 28 may include at least one program product having a set (e.g.,at least one) of program modules that are configured to carry out thefunctions of embodiments of the invention.

The embodiments of the invention may be implemented as a computerreadable signal medium, which may include a propagated data signal withcomputer readable program code embodied therein (e.g., in baseband or aspart of a carrier wave). Such a propagated signal may take any of avariety of forms including, but not limited to, electro-magnetic,optical, or any suitable combination thereof. A computer readable signalmedium may be any computer readable medium that is not a computerreadable storage medium and that can communicate, propagate, ortransport a program for use by or in connection with an instructionexecution system, apparatus, or device.

Program code embodied on a computer readable medium may be transmittedusing any appropriate medium including, but not limited to, wireless,wireline, optical fiber cable, radio-frequency (RF), etc., or anysuitable combination of the foregoing.

Program/utility 40, having a set (at least one) of program modules 42,may be stored in memory 28 by way of example, and not limitation, aswell as an operating system, one or more application programs, otherprogram modules, and program data. Each of the operating system, one ormore application programs, other program modules, and program data orsome combination thereof, may include an implementation of a networkingenvironment. Program modules 42 generally carry out the functions and/ormethodologies of embodiments of the invention as described herein.

Computer system/server 12 may also communicate with one or more externaldevices 14 such as a keyboard, a pointing device, a display 24, etc.;one or more devices that enable a consumer to interact with computersystem/server 12; and/or any devices (e.g., network card, modem, etc.)that enable computer system/server 12 to communicate with one or moreother computing devices. Such communication can occur via I/O interfaces22. Still yet, computer system/server 12 can communicate with one ormore networks such as a local area network (LAN), a general wide areanetwork (WAN), and/or a public network (e.g., the Internet) via networkadapter 20. As depicted, network adapter 20 communicates with the othercomponents of computer system/server 12 via bus 18. It should beunderstood that although not shown, other hardware and/or softwarecomponents could be used in conjunction with computer system/server 12.Examples include, but are not limited to: microcode, device drivers,redundant processing units, external disk drive arrays, RAID systems,tape drives, and data archival storage systems, etc.

Referring now to FIG. 2, illustrative cloud computing environment 50 isdepicted. As shown, cloud computing environment 50 comprises one or morecloud computing nodes 10 with which local computing devices used bycloud consumers, such as, for example, personal digital assistant (PDA)or cellular telephone 54A, desktop computer 54B, laptop computer 54C,and/or automobile computer system 54N may communicate. Nodes 10 maycommunicate with one another. They may be grouped (not shown) physicallyor virtually, in one or more networks, such as private, community,public, or hybrid clouds as described hereinabove, or a combinationthereof. This allows cloud computing environment 50 to offerinfrastructure, platforms, and/or software as services for which a cloudconsumer does not need to maintain resources on a local computingdevice. It is understood that the types of computing devices 54A-N shownin FIG. 2 are intended to be illustrative only and that computing nodes10 and cloud computing environment 50 can communicate with any type ofcomputerized device over any type of network and/or network addressableconnection (e.g., using a web browser).

Referring now to FIG. 3, a set of functional abstraction layers providedby cloud computing environment 50 (FIG. 2) is shown. It should beunderstood in advance that the components, layers, and functions shownin FIG. 3 are intended to be illustrative only and embodiments of theinvention are not limited thereto. As depicted, the following layers andcorresponding functions are provided:

Hardware and software layer 60 includes hardware and softwarecomponents. Examples of hardware components include mainframes. In oneexample, IBM® zSeries® systems and RISC (Reduced Instruction SetComputer) architecture based servers. In one example, IBM pSeries®systems, IBM System x® servers, IBM BladeCenter® systems, storagedevices, networks, and networking components. Examples of softwarecomponents include network application server software. In one example,IBM WebSphere® application server software and database software. In oneexample, IBM DB2® database software. (IBM, zSeries, pSeries, System x,BladeCenter, WebSphere, and DB2 are trademarks of International BusinessMachines Corporation registered in many jurisdictions worldwide.)

Virtualization layer 62 provides an abstraction layer from which thefollowing examples of virtual entities may be provided: virtual servers;virtual storage; virtual networks, including virtual private networks;virtual applications and operating systems; and virtual clients.

In one example, management layer 64 may provide the functions describedbelow. Resource provisioning provides dynamic procurement of computingresources and other resources that are utilized to perform tasks withinthe cloud computing environment. Metering and pricing provide costtracking as resources are utilized within the cloud computingenvironment, and billing or invoicing for consumption of theseresources. In one example, these resources may comprise applicationsoftware licenses. Security provides identity verification for cloudconsumers and tasks, as well as protection for data and other resources.Consumer portal provides access to the cloud computing environment forconsumers and system administrators. Service level management providescloud computing resource allocation and management such that requiredservice levels are met. Service Level Agreement (SLA) planning andfulfillment provides pre-arrangement for, and procurement of, cloudcomputing resources for which a future requirement is anticipated inaccordance with an SLA. Further shown in management layer is commandidentification, which represents the functionality that is providedunder the embodiments of the present invention.

Workloads layer 66 provides examples of functionality for which thecloud computing environment may be utilized. Examples of workloads andfunctions which may be provided from this layer include: mapping andnavigation; software development and lifecycle management; virtualclassroom education delivery; data analytics processing; transactionprocessing; and consumer data storage and backup. As mentioned above,all of the foregoing examples described with respect to FIG. 3 areillustrative only, and the invention is not limited to these examples.

It is understood that all functions of the present invention asdescribed herein typically may be performed by the commandidentification functionality (of management layer 64, which can betangibly embodied as modules of program code 42 of program/utility 40(FIG. 1). However, this need not be the case. Rather, the functionalityrecited herein could be carried out/implemented and/or enabled by any ofthe layers 60-66 shown in FIG. 3.

It is reiterated that although this disclosure includes a detaileddescription on cloud computing, implementation of the teachings recitedherein are not limited to a cloud computing environment. Rather, theembodiments of the present invention are intended to be implemented withany type of networked computing environment now known or laterdeveloped.

Referring now to FIG. 4, a system diagram describing the functionalitydiscussed herein according to an embodiment of the present invention isshown. It is understood that the teachings recited herein may bepracticed within any type of networked computing environment 86 (e.g., acloud computing environment 50). A stand-alone computer system/server 12is shown in FIG. 4 for illustrative purposes only. In the event theteachings recited herein are practiced in a networked computingenvironment 86, each client need not have a command identificationengine (engine 70). Rather, engine 70 could be loaded on a server orserver-capable device that communicates (e.g., wirelessly) with theclients to provide device protection therefor. Regardless, as depicted,engine 70 is shown within computer system/server 12. In general, engine70 can be implemented as program/utility 40 on computer system 12 ofFIG. 1 and can enable the functions recited herein. As further shown,engine 70 comprises a rules and/or computational engine that processes aset (at least one) of rules 78 and/or provides command identificationhereunder. It is further understood that command identification engine70 may be incorporated within or work in conjunction with any type ofsystem that receives, processes and/or executes commands with respect tovirtual resources in a networked computing environment. Such othersystem(s) have not been shown in FIG. 4 for brevity purposes.

Along these lines, engine 70 may perform multiple functions similar to ageneral-purpose computer. Specifically, among other functions, engine 70may: receive, in a computer memory medium (e.g., 28 of FIG. 1), a set ofcommands (e.g., from users 88A-N) for an instance 74 of virtual resource72 in the networked computing environment 86; analyze the set ofcommands to identify information 82A-N pertaining to the set ofcommands, the information 82A-N identifying at least one of thefollowing: the set of commands, a date/time stamp associated with theset of commands, relationship artifacts associated with the set ofcommands, and a set of tags associated with the set of commands; storethe information 82A-N in a computer storage device 80; execute at leastone of the set of commands against the instance 74; receive, from arequester 90, a request to access at least a subset of the information;retrieve the at least a subset 84 of the information 82A-N from thecomputer storage device 80 to generate a set of suggested commands95A-N; provide the set of suggested commands 95A-N to the requester 90;display the set of suggested commands 95A-N in a user interfaceaccessible to the requester 90; display the at least the subset 84 ofthe information 82A-N within the virtual resource 72; refine the atleast a subset 84 of the information 82A-N to generate the set ofsuggested commands 95A-N based on at least one of the following: a levelof use of the set of commands, a time since the instance 74 wasprovisioned, a relative order of the set of commands, a commonmiddleware installed across different images of the instance 74, newlyinstalled middleware, and an installation topology of the commonmiddleware and the newly installed middleware; and/or execute at leastone of the set of suggested commands 95A-N on another instance 76 of thevirtual resource 72.

Illustrative Examples

This section will describe illustrative examples of different scenariosin which the embodiments of the present invention can be carried out. Itis understood in advance that the teachings recited herein are notintended to be limited to any particular scenario.

-   -   1. A cloud management provider (e.g., a company) implements        engine 70.    -   2. Individuals/companies using a cloud resource provided by the        cloud management provider can opt into transmitting command        information back to engine 70.        -   A. Preferences could be set such as:            -   1. Denied lists of commands not to share;            -   2. A threshold of uses before a command is shared (e.g.,                only share after I've used a command 15 times);            -   3. Directories from which the command was executed to                determine whether to share or not to share. (e.g., if                from/home/private, don't share); and/or            -   4. Keywords such that it is permissible to share                commands that include the word “start” or “shutdown.”    -   3. A user logs into the cloud resource and executes a command.    -   4. If enabled, the command is both executed against the cloud        resource and sent to the engine 70.    -   5. The engine 70 continually collects data such as:        -   A. Incoming commands;        -   B. The directory/path in which the command was executed;        -   C. The instance against which the command was executed;        -   D. Tags associated with the commands. (e.g., the user would            tag start-dfs.sh with “start Hadoop” so other users know            that the command starts Hadoop);        -   E. The geographical location where the command was executed;        -   F. A time instance 74 has been running;        -   G. An order of commands entered;        -   H. A success/failure measurement from excuting the commands;        -   I. Middleware/software of the system which the base image            had on them already—such information can be simply gathered            as image artifacts;        -   J. Newly installed middleware/software on the system which            were not part of installation from the base image—such            information can be gathered by agent scanning and passing            the information back to the cloud management system; and        -   K. Configuration and deployment (installation) topology of            those middleware/software. The system can see if one is in a            cluster environment and if so, primary, secondary, and so            on, including how many members in a cluster, etc. Such            information can be well defined by each middleware/software            for what information is appropriate to gather and helpful to            the system for cloud crowd command.    -   6. Optionally, highly simple commands (e.g., Is-al) may be        ignored by the system.    -   7. If another user wishes to view commands identified via crowd        sourcing they may do so at any time, e.g., those:        -   A. Displayed within a cloud management area associated with            each image; and/or        -   B. Displayed within the resource either:            -   1. From a pull mechanism;            -   2. As deployed as an artifact at instance creation time;            -   3. As a user begins to type a command; and/or            -   4. As a stand-alone asset associated with the resource.    -   8. Commands may be further refined based on:        -   A. Location of the user in comparison with location where            executed (e.g., view commands entered by other users located            in Dallas, Tex.);        -   B. Geographic location of the cloud user (e.g., other            individuals similar to you ran the following commands);        -   C. Popularity;        -   D. Keyword;        -   E. Expertise level of users executing the command;        -   F. A level of use of the set of commands;        -   G. A time since the instance was provisioned;        -   H. A relative order of the set of commands;        -   I. A common middleware installed across different images of            the instance;        -   J. Newly installed middleware; and        -   K. An installation topology of the common middleware and the            newly installed middleware.

These concepts will be further illustrated in conjunction with FIG. 5,which demonstrates additional logic (i.e., related artifacts) providedto the cloud crowd command information. That is, engine 70 (FIG. 4)allows a user to create “patterns” of components which correspond tocollections of virtual machines, each performing a unique function andcomprising a unique OS, middleware and software, etc. When such apattern is used in cloud computing environment 50, there are oftencommand line commands which are unique or closely related to thatspecific pattern. Engine 70 detects if a virtual machine exists as partof a pattern, and then associates all of the commands entered by a userto that pattern.

As shown in FIG. 5, engine 70 analyzes relationship artifacts to providea process for enhanced command management in the cloud computingenvironment 50 (FIG. 4). In this embodiment, the following steps areperformed:

-   -   A. A set of crowd cloud commands is gathered (i.e., step 501);    -   B. Additional information about the instance is gathered (i.e.,        step 502) such as:        -   1. Middleware/software of the system which the base image            had on them already—such information can be simply gathered            as image artifacts;        -   2. Newly installed middleware/software on the system which            were not part of installation from the base image—such            information can be gathered by agent scanning and passing            those information back to the cloud management system; and        -   3. Configuration and deployment (installation) topology of            the middleware/software. The system can see if one is in a            cluster environment and if so, primary, secondary, and so            on, including how many members in a cluster. Such            information can be well defined by each middleware/software            for what information is appropriate to gather and helpful to            the system for cloud crowd command;    -   C. Display the most popular or frequent commands executed        against an instance, including the order of the commands entered        (i.e., step 503);    -   D. Observe a state of the instance by its role in the system        (e.g., such as member of cluster, or primary for database or        service, etc.) (i.e., step 504);    -   E. Perform an analysis of all commands run by instances (i.e.,        step 505);    -   F. Group the commands by middleware/software, as well as by role        in the system (i.e., step 506);    -   G. Display the most relevant command run by other instances with        same artifacts when a user selects an instance in question and        asks for a common crowd command (i.e., step 507); and    -   H. Display a set of filters according to types of installations        and configurations to show only commands relevant to the        particular role of that installation, such as a cluster member.        The engine can suggest the right set of filters or the user can        choose the filter that they prefer to see (i.e., step 508).

This approach is beneficial because commands could be vastly different,e.g., while configuring a Websphere node based on the relationships thatthe Websphere node has with other nodes (artifacts). If a particularWebsphere node is part of a cluster (e.g., Websphere XD) the steps willbe different than if that node is isolated. Additional relationshipswill imply a different set of commands: Websphere->DB/2 vsWebsphere->MySQL could have some effects as well. Therefore, engine 70is configured to analyze the deployed pattern and further narrow downthe recommended commands that a user might need. Engine 70 may suggestcommands based on common middleware installed across different images.This could be enabled using “tagging” to apply a term to a command afterit's executed for sharing purposes. Engine 70 could tag with themiddleware, ex. DB2, and then all images that have DB2 installed mightshow that command regardless of how often it is used by others having aninstance of the image.

Consider the process flow 600 shown in FIG. 6, wherein a user may selectan instance with DB2 installation in which the DB2 has been configuredto be a primary with another secondary node in a different instance. Inthis case, the user may want to see how the DB2 primary can manuallysync data with the secondary node. Engine 70 shows all the commandsother instances have from DB2 at 601. Next, at 602, the system (i.e.,engine 70) suggests a filtered command set based on installation orconfiguration characteristics, or the user selects a filter and thecharacteristic of being a primary node of DB2 with another secondarynode. Then, at 603, engine 70 shows only those relevant commands thatwere run from primary nodes of DB2 with another secondary node.

Referring now to FIGS. 4 and 7, another embodiment for providingadditional logic to the cloud crowd command information based onrelative elapsed time is shown. In this embodiment, engine 70 starts bylogging each command and associating a date/time stamp with it. Engine70 takes this date/time and then derives a relative time, for example,the time since the VM was created. Now each command has an order ofoperations as well as a relative time executed. This allows cloud usersto save off the commands as groups or scripts to be executed quicklyagainst their instances. Statistics may show, for example, that CommandY is usually only executed 10 minutes after Command X, and if executedearlier than that, has a high probability of failing (e.g., starting aservice before the previous command finished compiling some code).Therefore, in exemplary embodiments, when the user gets his/her instance74 and needs to perform an operation, engine 70 can not only recommendthe most common commands that others used, but can also recommend asuggested order of commands, wherein the relative time can also be usedto augment pure ordered structure.

Consider another example in which 30 minutes after logging in to virtualresource 72 for the first time engine 70 recommends a specific set ofcommands which are the most commonly executed. The combined commands arethen optionally saved into a script and a user can view an option to“run startup script” which could run those command that were commonlyrun within x minutes of installing a new instance. Similarly, a group ofcommands might fall into another script for shutdown type commands basedon the date/time, etc.

As shown in FIG. 7, engine 70 analyses a relative elapsed time toprovide a process 700 for enhanced command management in the cloudcomputing environment 50 (FIG. 4). In this embodiment, the followingsteps are performed:

-   -   A. A set of crowd cloud commands are gathered (i.e., step 701).    -   Additional information about the instance is gathered such as:        -   1. Time the instance has been running;        -   2. Order of commands entered; and        -   3. Success and failure responses from executing the            commands;    -   B. Display the most popular or frequent commands executed        against an instance, including the order of the commands entered        (i.e., step 702);    -   C. Group commands and save to one or more scripts based on the        time since the instance was provisioned and the relative order        of the set of commands (i.e., step 703), e.g., those commands        executed within 10 minutes to logging into the instance can be        saved off to a startup script. Or, if the commands tend to be        executed within a certain amount of time or order before an        instance is stopped, those commands can be saved off to a        shutdown script. If other commands tend to be grouped or        immediately executed within a preferred time they could also be        saved as a script to run together;    -   D. Save the command script(s) (i.e., step 704)        -   1. within each instance or, if saved within each            image/instance, the user might type a predefined run command            to initiate the script such as CloudStartup or            CloudShutdown; or        -   2. made available through the cloud management portal; and    -   E. Optionally, instance owners may pick and choose or turn off        commands that appear as part of a script or command grouping to        customize for their environment.

In one embodiment, a statistical probability of success can be assignedto each of the set of suggested commands 95A-N (FIG. 4). For example,the commands can have a statistical probability of success based oncommands executed before it. Using this information a user could “ping”a command before actually executing it to determine whether it might besuccessful. In the case of WebSphere, a user cannot start a server ifthe node the server is running on hasn't previously been started.Therefore, engine 70 might predict an 80% chance of failure for a userwho wishes to check to see if a “startServer.sh” command will complete.The user might see a user experience area within their cloud portal (notshown) listing all of the most popular commands followed by agreen/red/orange/yellow icon to suggest the probability it will besuccessful.

Referring now to FIG. 8, a flow diagram 800 for command valuesubstitutions according to embodiments of the present invention isshown. This embodiment applies to more general command valuesubstitutions, such as a port in an iptables command. The methodoutlined in flow diagram 800 can apply to any command that containsvalues, which are variable and can be identified by a flag within thecommand or by the context of its placement within the command. Themethod steps for doing so are outlined as follows:

-   -   A. A set of crowd cloud commands are gathered (i.e., step 801);    -   B. Correlate commands which are the same, but may differ in        flags provided and values of the flags provided (i.e., step        802). For example, the following iptables rules where some        values of the flags differ and some of the values are the same:        -   iptables -A INPUT -p tcp -s 10.2.3.4 --dport 80 -j ACCEPT        -   iptables -A INPUT -p tcp -s 10.2.3.7 --dport 443 -j ACCEPT        -   iptables -A INPUT -p tcp -s 10.2.3.8 --dport 8080 -j ACCEPT    -   C. Analyze flags accompanied and their values (i.e., step 803).        For example, the above command iptables command flags can be        analyzed by determining the flag name frequency of flag used        most common value(s) and frequency value of other flags commonly        accompanied by:        -   -A 80% of time INPUT 99% of the time -p, -s, --dport, -j        -   -p 75% of time tcp 85% of time -A, -s, --dport -j        -   -s 70% of time --- varies 95% of time -A, -p, --dport, -j        -   -dport 75% of time 80, 443 40% of time, 40% of time -A, -p,            -s, -j        -   -j 80% of time ACCEPT, DROP 80%, 20% -A, -p, -s, --dport    -   D. Based on the above analysis, the system, when suggesting to        the user to use the “iptables” command, will also suggest flags        to use with it and vary it's suggestion on the values of the        flags based on past statistics (i.e., step 804), e.g.,        -   The system will suggest for the user to use the “-A” flag            with the “INPUT” flag because it is very frequently used in            that fashion, with that value.        -   Because the “-s” flag has a value that almost always varies,            it will prompt the user for the IP address to substitute            here instead of automatically populating it.

Referring now to FIG. 9, consider the following flow diagram 900 inlight of the command value substitution shown in FIG. 8. In this case,shutdown, startup and other commands often include a username and/orpassword entered along with it. Sometimes, this username and password iscommon among the same type of applications and cloud instances. Othertimes, they will be unique and private to a user. As part of the overallcommand suggestion process, engine 70 can also scan for probableusernames and passwords within the history of commands, and decidewhether to automatically provide the same username and password for theuser as part of the command, or prompt the user to enter in his/her own.In this embodiment, the following steps are performed:

-   -   A. Engine 70 recognizes that a username or password is part of a        command (i.e., step 901) by such methods as:        -   1. The presence of a “-username” or “-password” flag, or            something similar,        -   2. Any other known methods for password identification, such            as an encrypted or “x-ed” out field;    -   B. For the username, compare history of the commands (i.e., step        902) and check to see if the same username tends to be used        consistently (e.g., “db2inst1”) or if it tends to differ by user        (i.e., “johndoe”);    -   C. At 903, it is determined if the same user ID is provided        consistently for that command. If yes, that ID can continue to        be used (i.e., 904);    -   D. If the ID tends to differ, it can instead do either of:        -   a. Prompt the user for the correct ID to use instead (i.e.,            905), or        -   b. Run some analytics to see if there is a pattern or            relation between the ID used in this command and perhaps an            ID of the user known to the system, such as the user's cloud            ID, and use that instead (i.e., 906).    -   E. For the password, security would typically mandate that it        would not be retained in plain text. Therefore, passwords when        stored in the database history of commands can be encrypted, and        in the future, the encrypted values can be compared to see if        they consistently are equal in value. If so, this password can        be utilized in the command as well, Otherwise, the user would be        prompted for a new password.

Referring now to FIG. 10, a method flow 1000 according to an embodimentof the present invention is shown. In step 1001, a set of commands isreceived for an instance of a virtual resource in the networkedcomputing environment. In step 1002, the set of commands is analyzed toidentify information pertaining to the set of commands, the informationidentifying at least one of the following: the set of commands, adate/time stamp associated with the set of commands, relationshipartifacts associated with the set of commands, and a set of tagsassociated with the set of commands. In step 1003, the information isstored in a computer storage device. In step 1004, a request is receivedfrom a requester to access at least a subset of the information. In step1005, the at least a subset of the information from the computer storagedevice is retrieved to generate a set of suggested commands. In step1006, the set of suggested commands are refined based on at least one ofthe following: a level of use of the set of commands, a time since theinstance was provisioned, a relative order of the set of commands, acommon middleware installed across different images of the instance,newly installed middleware, and an installation topology of the commonmiddleware and the newly installed middleware. In step 1007, the set ofsuggested commands is provided to the requester.

While shown and described herein as a command identification solution,it is understood that the invention further provides various alternativeembodiments. For example, in one embodiment, the invention provides acomputer-readable/useable medium that includes computer program code toenable a computer infrastructure to provide command identificationfunctionality as discussed herein. To this extent, thecomputer-readable/useable medium includes program code that implementseach of the various processes of the invention. It is understood thatthe terms computer-readable medium or computer-useable medium compriseone or more of any type of physical embodiment of the program code. Inparticular, the computer-readable/useable medium can comprise programcode embodied on one or more portable storage articles of manufacture(e.g., a compact disc, a magnetic disk, a tape, etc.), on one or moredata storage portions of a computing device, such as memory 28 (FIG. 1)and/or storage system 34 (FIG. 1) (e.g., a fixed disk, a read-onlymemory, a random access memory, a cache memory, etc.).

In another embodiment, the invention provides a method that performs theprocess of the invention on a subscription, advertising, and/or feebasis. That is, a service provider, such as a Solution Integrator, couldoffer to provide command identification functionality. In this case, theservice provider can create, maintain, support, etc., a computerinfrastructure, such as computer system 12 (FIG. 1) that performs theprocesses of the invention for one or more consumers. In return, theservice provider can receive payment from the consumer(s) under asubscription and/or fee agreement and/or the service provider canreceive payment from the sale of advertising content to one or morethird parties.

In still another embodiment, the invention provides acomputer-implemented method for command identification. In this case, acomputer infrastructure, such as computer system 12 (FIG. 1), can beprovided and one or more systems for performing the processes of theinvention can be obtained (e.g., created, purchased, used, modified,etc.) and deployed to the computer infrastructure. To this extent, thedeployment of a system can comprise one or more of: (1) installingprogram code on a computing device, such as computer system 12 (FIG. 1),from a computer-readable medium; (2) adding one or more computingdevices to the computer infrastructure; and (3) incorporating and/ormodifying one or more existing systems of the computer infrastructure toenable the computer infrastructure to perform the processes of theinvention.

As used herein, it is understood that the terms “program code” and“computer program code” are synonymous and mean any expression, in anylanguage, code, or notation, of a set of instructions intended to causea computing device having an information processing capability toperform a particular function either directly or after either or both ofthe following: (a) conversion to another language, code, or notation;and/or (b) reproduction in a different material form. To this extent,program code can be embodied as one or more of: an application/softwareprogram, component software/a library of functions, an operating system,a basic device system/driver for a particular computing device, and thelike.

A data processing system suitable for storing and/or executing programcode can be provided hereunder and can include at least one processorcommunicatively coupled, directly or indirectly, to memory elementsthrough a system bus. The memory elements can include, but are notlimited to, local memory employed during actual execution of the programcode, bulk storage, and cache memories that provide temporary storage ofat least some program code in order to reduce the number of times codemust be retrieved from bulk storage during execution. Input/outputand/or other external devices (including, but not limited to, keyboards,displays, pointing devices, etc.) can be coupled to the system eitherdirectly or through intervening device controllers.

Network adapters also may be coupled to the system to enable the dataprocessing system to become coupled to other data processing systems,remote printers, storage devices, and/or the like, through anycombination of intervening private or public networks. Illustrativenetwork adapters include, but are not limited to, modems, cable modems,and Ethernet cards.

The foregoing description of various aspects of the invention has beenpresented for purposes of illustration and description. It is notintended to be exhaustive or to limit the invention to the precise formdisclosed and, obviously, many modifications and variations arepossible. Such modifications and variations that may be apparent to aperson skilled in the art are intended to be included within the scopeof the invention as defined by the accompanying claims.

What is claimed is:
 1. A computer-implemented method for identifyingcommands for virtual resource instances in a networked computingenvironment, comprising: analyzing a set of commands to identifyinformation pertaining to the set of commands, the informationidentifying at least one of the following: the set of commands, adate/time stamp associated with the set of commands, relationshipartifacts associated with the set of commands, and a set of tagsassociated with the set of commands; receiving, from a requester, arequest to access at least a subset of the information; retrieving theat least a subset of the information from a computer storage device togenerate a set of suggested commands; and providing the set of suggestedcommands to the requester.
 2. The computer-implemented method of claim1, further comprising refining the at least a subset of the informationto generate the set of suggested commands based on at least one of thefollowing: a level of use of the set of commands, a time since theinstance was provisioned, a relative order of the set of commands, acommon middleware installed across different images of the instance,newly installed middleware, and an installation topology of the commonmiddleware and the newly installed middleware.
 3. Thecomputer-implemented method of claim 2, further comprising: assembling asubset of the set of suggested commands into a script based on the timesince the instance was provisioned and the relative order of the set ofcommands.
 4. The computer-implemented method of claim 1, furthercomprising: analyzing a set of flags and flag values for the set ofcommands; and generating a suggested set of flags for the suggested setof commands based on the analyzing.
 5. The computer-implemented methodof claim 1, further comprising executing at least one of the set ofsuggested commands against the instance.
 6. The computer-implementedmethod of claim 1, further comprising assigning a statisticalprobability of success to each of the set of suggested commands.
 7. Thecomputer-implemented method of claim 1, the networked computingenvironment comprising a cloud computing environment and the set ofcommands comprising a set of commands utilized within a cloud computingenvironment.
 8. A system for identifying commands for virtual resourceinstances in a networked computing environment, comprising: a memorymedium comprising instructions; a bus coupled to the memory medium; anda processor coupled to the bus that when executing the instructionscauses the system to: analyze a set of commands to identify informationpertaining to the set of commands, the information identifying at leastone of the following: the set of commands, a date/time stamp associatedwith the set of commands, relationship artifacts associated with the setof commands, and a set of tags associated with the set of commands;receive, from a requester, a request to access at least a subset of theinformation; retrieve the at least a subset of the information from acomputer storage device to generate a set of suggested commands; andprovide the set of suggested commands to the requester.
 9. The system ofclaim 8, the memory medium further comprising instructions for causingthe system to refine the at least a subset of the information togenerate the set of suggested commands based on at least one of thefollowing: a level of use of the set of commands, a time since theinstance was provisioned, a relative order of the set of commands, acommon middleware installed across different images of the instance,newly installed middleware, and an installation topology of the commonmiddleware and the newly installed middleware.
 10. The system of claim9, the memory medium further comprising instructions for causing thesystem to assemble a subset of the set of suggested commands into ascript based on the time since the instance was provisioned and therelative order of the set of commands.
 11. The system of claim 8, thememory medium further comprising instructions for causing the system to:analyze a set of flags and flag values for the set of commands; andgenerate a suggested set of flags for the suggested set of commandsbased on the analyzing.
 12. The system of claim 8, the memory mediumfurther comprising instructions for causing the system to execute atleast one of the set of suggested commands against the instance.
 13. Thesystem of claim 8, the memory medium further comprising instructions forcausing the system to assign a statistical probability of success toeach of the set of suggested commands.
 14. The system of claim 8, thenetworked computing environment comprising a cloud computing environmentand the set of commands comprising a set of commands utilized within acloud computing environment.
 15. A computer program product foridentifying commands for virtual resource instances in a cloud computingenvironment, the computer program product comprising a computer readablestorage media, and program instructions stored on the computer readablestorage media, to: analyze a set of commands to identify informationpertaining to the set of commands, the information identifying at leastone of the following: the set of commands, a date/time stamp associatedwith the set of commands, relationship artifacts associated with the setof commands, and a set of tags associated with the set of commands;receive, from a requester, a request to access at least a subset of theinformation; retrieve the at least a subset of the information from acomputer storage device to generate a set of suggested commands; andprovide the set of suggested commands to the requester.
 16. The computerprogram product of claim 15, the computer readable storage media furthercomprising instructions to refine the at least a subset of theinformation to generate the set of suggested commands based on at leastone of the following: a level of use of the set of commands, a timesince the instance was provisioned, a relative order of the set ofcommands, a common middleware installed across different images of theinstance, newly installed middleware; and an installation topology ofthe common middleware and the newly installed middleware.
 17. Thecomputer program product of claim 16, the computer readable storagemedia further comprising instructions to assemble a subset of the set ofsuggested commands into a script based on the time since the instancewas provisioned and the relative order of the set of commands.
 18. Thecomputer program product of claim 15, the memory medium furthercomprising instructions for causing the system to: analyze a set offlags and flag values for the set of commands; and generate a suggestedset of flags for the suggested set of commands based on the analyzing.19. The computer program product of claim 15, the memory medium furthercomprising instructions for causing the system to assign a statisticalprobability of success to each of the set of suggested commands.
 20. Thecomputer program product of claim 15, the memory medium furthercomprising instructions for causing the system to receive at least onecommand from the requester, the at least one command being identifiedbased on the at least a subset of the information.